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2010-04-17 1 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

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Page 1: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

2010-04-17 1• Prof. I. J. Chung• Dept. of Computer & Information Science, Korea

Univ.

Collective Intelligence

By Yunfeng Pei

Page 2: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Collective Intelligence

Concept집단지성 ( 集体智慧 /collective intelligence) 란 다수의 개체들이 서로 협력 혹은 경쟁을 통하여 얻게 되는 지적 능력에 의한 결과로 얻어진 집단적 능력을 말한다 .

집단적 지적 능력을 통해 개체적으로는 미미하게 보이는 동물 , 사람의 능력을 모으는 과정을 통한 결정 능력의 다양한 형태로 한 개체의 능력 범위를 넘어선 힘을 발휘할 수도 있다고 , 이 분야는 사회학 , 경영학 , 컴퓨터 공학 등에서 연구되고 있다 .

23年 4月 19日 2• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 3: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Collective Intelligence

History1910 년대 하버드 대학 교수이자 곤충학자인 William Morton Wheeler 가 개미의 사회적 행동을 관찰하면서 처음 제시했다 .

휠러는 개체로는 미미한 개미가 공동체로서 협업 ( 協業 ) 하여 거대한 개미집을 만들어내는 것을 관찰하였고 , 이를 근거로 개미는 개체로서는 미미하지만 군집 (群集 ) 하여서는 높은 지능체계를 형성한다고 설명하였다 .

Pierre Levy 는 사이버 공간의 집단지성을 제시하였다 .

그는 " 누구나 자신의 공간 ( 사이트 ) 를 가지고 일종의 형성하는 시대가 오면 어디에나 분포하고 , 지속적으로 가치 부여되며 , 실시간으로 조정되고 , 역량의 실제적 동원에 이르는 집단지성이 발현될 것 " 이라고 주장하였다 .

23年 4月 19日 3• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 4: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Collective Intelligence

Four principles CI 는 대규모 협조이다 . 이런 계념을 실현하기 위해서는 4가지 기본 원칙이 필요하다 .

Openness Peering (对等 ) Sharing Acting globally

23年 4月 19日 4• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 5: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Collective Intelligence

Types

23年 4月 19日 5• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 6: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Collective Intelligence

Examples

Wikipedia Wikipedia 의 발전 과정은 지식 · 정보의 생산자나 수혜자가 따로 없이 누구나 생산할 수 있고 모두가 손쉽게 공유하면서도 정체되지 않고 계속 진보하는 , 집단지성의 특성을 보여준다 .

Google search웹 페이지 평가에 다른 페이지에서 얼마나 링크를 많이 받았는지를 적용한 첫 검색엔진이다 . 수천 명이 특정 웹 페이지에 대해 말한 정보를 랭킹 방법에 적용하여 검색 결과 순서를 정하는 데 이용했다 .

Web 2.0

23年 4月 19日 6• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 7: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Collective Intelligence

Benefits of collective intelligenceHigher retention rates

The more users interact with the application, the stickier it gets for them, and the higher the probability that they’ll become repeat visitors.

Greater opportunities to market to the userThe greater the number of interactions, the greater the number of pages visited by the user, which increases the opportunities to market to or communicate with the user.

23年 4月 19日 7• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 8: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Collective Intelligence

Benefits of collective intelligenceHigher probability of a user completing a transaction and finding information of interest

The more contextually relevant information that a user finds, the better the chances that he’ll have the information he needs to complete the transaction or find content of interest. This leads to higher click-through and conversion rates for your advertisements.

Boosting search engine rankingsThe more users participate and contribute content, the more content is available in your application and indexed by search engines. This could boost your search engine ranking and make it easier for others to find your application.

23年 4月 19日 8• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 9: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Collective Intelligence

CI in web applicationsThree things that need to happen to apply collective intelligence in your application.

Allow users to interact with your site and with each other, learning about each user through their interactions and contributions.Aggregate what you learn about your users and their contributions using some useful models.Leverage those models to recommend relevant content to a user.

23年 4月 19日 9• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 10: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Collective Intelligence

CI in web applicationsThree components to harnessing collective intelligence.

Allow users to interact.Learn about your users in aggregate.Personalize content using user interaction data and aggregate data.

23年 4月 19日 10• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 11: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

2010-04-17 11• Prof. I. J. Chung• Dept. of Computer & Information Science, Korea

Univ.

Social Network

By Yunfeng Pei

Page 12: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Social Network

ConceptSocial Network 는 web science 의 연구 분야 중 하나로 , web 상에서 개인 또는 집단이 하나의 노드 (node) 가 되어 각 노드들 간의 상호의 존적인 관계 (tie) 에 의해 만들어지는 사회적 관계 구조를 말한다 .

Node 는 network 에서 존재하는 개별적인 주체들이다 .

Tie 는 각 node 들의 관계를 말한다 .

23年 4月 19日 12• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 13: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Social Network

Social network analysis - SNASocial network analysis 사람과 사람들 간의 중요한 지식관계를 반영하며 , 특별히 조직간의 협조를 향상시키고 , 지식을 창조하며 , 지식을 전파한다 .

Social network analysis 는 수많은 노드들과 그 노드들 사이의 무수히 다양한 관계들로 인해 계산론적으로 접근하기에 매우 복잡한 분야이다 .

Social network analysis 는 현재 중요한 기술로 거듭나고 있다 . 그리고 또한 이슈되는 연구분야이다 .

23年 4月 19日 13• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 14: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Social Network

Social network analysisSolve some problems

Choose a leader 어떠한 사람이 수많은 사람들 중에서 신뢰성이 높고 존경을 받는 것인가 ?

  

Choose a task team어떻게 하면 조직네에서 연결이 있는 사람들을 하나의 팀으로 조성하는가 ?

Mergers & Acquisitions두 문화가 합병되는 것만이 아니라 , 두 독립적인 네트워크를 합병하는 것이다 .

23年 4月 19日 14• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 15: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Social Network

23年 4月 19日 15• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

An example of a social network diagram.

Page 16: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Social Network

Social network analysisBetweenness

A node lies between other nodes in the network.The connectivity of the node's neighbors.Giving a higher value for nodes which bridge clusters.

BridgeAn edge is said to be a bridge if deleting it would cause its endpoints to lie in different components of a graph.

23年 4月 19日 16• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 17: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Social Network

Social network analysisCloseness

The degree an individual is near all other individuals in a network. It reflects the ability to access information. Thus, closeness is the inverse of the sum of the shortest distances between each individual and every other person in the network.

23年 4月 19日 17• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 18: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Social Network

Social network analysisDegree

The count of the number of ties to other actors in the network. Network or global-level density is the proportion of ties in a network relative to the total number possible. The degree that a node contributes to sum of maximum flow between all pairs of nodes.

23年 4月 19日 18• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 19: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Social Network

Social network analysisCentralization

The difference between the number of links for each node divided by maximum possible sum of differences. A centralized network will have many of its links dispersed around one or a few nodes, while a decentralized network is one in which there is little variation between the number of links each node possesses.

23年 4月 19日 19• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 20: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Social Network

Social network analysisSocial network analysis software

Network analytic tools are used to represent the nodes (agents) and edges (relationships) in a network, and to analyze the network data.

Network analysis tools allow researchers to investigate large networks like the Internet, disease transmission, etc.

23年 4月 19日 20• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 21: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

2010-04-17 21• Prof. I. J. Chung• Dept. of Computer & Information Science, Korea

Univ.

The Semantic Web

By Yunfeng Pei

Page 22: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

The Semantic Web

Concept

The Semantic Web is an evolving development of the World Wide Web in which the meaning of information and services on the web is defined, making it possible for the web to "understand" and satisfy the requests of people and machines to use the web content.

23年 4月 19日 22• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 23: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

The Semantic Web

The difference The world wide web

Hypertext Markup Language (HTML).

HTML 로 작성된 contents 는 컴퓨터가 해석할수 있는 meta data 보다는 사람의 시각정보에 대한 meta data 와 자연어로 작성된 contents 로 되여있다 .

The semantic webResource Description Framework (RDF), Web Ontology Language (OWL),Extensible Markup Language (XML).

이런 언어를 기반으로 작성된 contents 는 컴퓨터가 해석할수 있는 meta data로 구성 .

23年 4月 19日 23• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 24: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

The Semantic Web

FactorOntology

Ontology 는 일종의 지식표현으로서 컴퓨터를 하여끔 ontology 로 표현된 개념을 이해하고 지식처리를 할 수 있는것이다 .

agent유저를 대신햐여 정보를 수집하고 , 정보를 검색하며 , ontology 를 이용하여 다른 agent 과 교류하여 유저대신에 일상 일를 처리하는 것이다 .agent 는 the semantic web 중에서 중요한 요소이다 .

23年 4月 19日 24• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 25: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

The Semantic Web

Components

23年 4月 19日 25• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 26: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

The Semantic Web

ComponentsXML

Extensible Markup Language. The language framework that has been used to define nearly all new languages that are used to interchange data over the web.

XML SchemaA language used to define the structure of specific XML languages.

RDFA flexible language capable of describing all sorts of information and meta data.

23年 4月 19日 26• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 27: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

The Semantic Web

ComponentsRDF Schema

A framework that provides a means to specify basic vocabularies for specific RDF application languages to use.

RDF Schema is a framework for constructing ontologies and is used by many more advanced ontology frameworks.

OntologyLanguages used to define vocabularies and establish the usage of words and terms in the context of a specific vocabulary.

23年 4月 19日 27• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 28: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

The Semantic Web

ComponentsLogic and Proof

Logical reasoning is used to establish the consistency and correctness of data sets and to infer conclusions that aren’t explicitly stated but are required by or consistent with a known set of data. Proofs trace or explain the steps of logical reasoning.

Trust A means of providing authentication of identity and evidence of the trustworthiness of data, services, and agents.

23年 4月 19日 28• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 29: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

The Semantic Web

Vision

The semantic web is a vision of information that is understandable by computers, so that users can perform more of the tedious work involved in finding, combining, and acting upon information on the web.

23年 4月 19日 29• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 30: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

The Semantic Web

ApplicationRSS(RDF Site Summary)Web blogPortalSearch EngineThe semantic web serviceBusiness IntelligenceKnowledge Management

23年 4月 19日 30• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 31: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

2010-04-17 31• Prof. I. J. Chung• Dept. of Computer & Information Science, Korea

Univ.

Ontology

By Yunfeng Pei

Page 32: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Ontology

ConceptIn theory

Ontologies are defined as a formal specification of a shared conceptualization.

In EnglishAn ontology provides a shared vocabulary, which can be used to model a domain, that is, the type of objects and/or concepts that exist, and their properties and relations.

23年 4月 19日 32• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 33: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Ontology

Components Class

sets, collections, concepts, classes in programming, types of objects, or kinds of things.

Instances

instances or objects

Relationways in which classes and individuals can be related to one another

Property aspects, properties, features, characteristics, or parameters that objects (and classes) can have

23年 4月 19日 33• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 34: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Ontology

Ontology languageRDF (Resource Description Framework)

RDF is a standard model for data interchange on the Web. RDF has features that facilitate data merging even if the underlying schemas differ, and it specifically supports the evolution of schemas over time without requiring all the data consumers to be changed.

OWL (Web Ontology Language)The W3C Web Ontology Language (OWL) is a Semantic Web language designed to represent rich and complex knowledge about things, groups of things, and relations between things.

23年 4月 19日 34• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 35: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Ontology

Ontology languageSWRL (Semantic Web Rule Language)

SWRL is a proposal for a Semantic Web rules-language, combining sublanguages of the OWL Web Ontology Language (OWL DL and Lite) with those of the Rule Markup Language.

23年 4月 19日 35• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 36: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Ontology

Perspectives Library and Information Science

Artificial Intelligence

Natural Language Processing

The Semantic Web

23年 4月 19日 36• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 37: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Ontology

Artificial IntelligenceObjectives

Model common sense and domain knowlege

UsageKnowledge representation and reasoning

ExamplesCYC,…

23年 4月 19日 37• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 38: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Ontology

The Semantic WebObjectives

Provide semantics for web resource

Usage Describe resources and their contents

Examples DC, DAML-library,…

23年 4月 19日 38• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 39: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Ontology

The Ontology Web Language – OWLGoal

Formally describe the semantics of classes and properties used in web documents.Go beyond the basic semantics in RDFS

Current statusUse cases and their requirements on ontologiesEight design goalsRequirements

23年 4月 19日 39• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 40: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Ontology

The Ontology Web Language – OWLDesign goals

Shared ontologiesOntology interoperabilityInconsistency detectionBalance of expressivity and scalabilityEase of useXML syntaxInternationalisation

23年 4月 19日 40• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.

Page 41: 2010-04-171 Prof. I. J. Chung Dept. of Computer & Information Science, Korea Univ. Collective Intelligence By Yunfeng Pei

Ontology

The Ontology Web Language – OWLRequirements

Ontologies as distinct objectsUnambiguous term referencing with URIsExplicit ontology extensionCommitment to ontologiesOntology metadataVersioning informationClass definition primitivesProperty definition primitivesDatatypes Class and property equivalenceLocal unique names assumptionEtc….

23年 4月 19日 41• Prof. I. J. Chung•Dept. of Computer & Information Science, Korea Univ.